Although there is evidence that significant sleep problems are common in children with autism spectrum disorder (ASD) and that poor sleep exacerbates problematic daytime behavior, such relationships have received very little attention in both research and clinical practice. Treatment guidelines to help manage challenging behaviors in ASD fail to mention sleep at all, or they present a very limited account. Moreover, limited attention is given to children with low-functioning autism, those individuals who often experience the most severe sleep disruption and behavioral problems. This paper describes the nature of sleep difficulties in ASD and highlights the complexities of sleep disruption in individuals with low-functioning autism. It is proposed that profiling ASD children based on the nature of their sleep disruption might help to understand symptom and behavioral profiles (or vice versa) and therefore lead to better-targeted interventions. This paper concludes with a discussion of the limitations of current knowledge and proposes areas that are important for future research. Treating disordered sleep in ASD has great potential to improve daytime behavior and family functioning in this vulnerable population.
We analyzed over 20,000 nights of sleep from 67 individuals with autism to investigate whether daytime behaviors can be predicted from prior sleep patterns. Better-than-chance accuracy was obtained for 81% of individuals, with measures of night-to-night variation in sleep timing and duration most relevant for accurate prediction. Our results highlight the importance of regular sleep patterns for better daytime functioning and represent a step toward the development of 'smart sleep technologies' to pre-empt behavior in individuals with autism.
Despite sleep disturbance being a common complaint in individuals with autism, specific sleep phenotypes and their relationship to adaptive functioning have yet to be identified. This study used cluster analysis to find distinct sleep patterns and relate them to independent measures of adaptive functioning in individuals with autism. Approximately 50,000 nights of care-giver sleep/wake logs were collected on school-days for 106 individuals with low functioning autism (87 boys, 14.77 ± 3.11 years) for 0.5–6 years (2.2 ± 1.5 years) from two residential schools. Using hierarchical cluster analysis, performed on summary statistics of each individual across their recording duration, two clusters of individuals with clearly distinguishable sleep phenotypes were found. The groups were summarized as ‘unstable’ sleepers (cluster 1, n = 41) and ‘stable’ sleepers (cluster 2, n = 65), with the former exhibiting reduced sleep duration, earlier sleep offset, and less stability in sleep timing. The sleep clusters displayed significant differences in properties that were not used for clustering, such as intellectual functioning, communication, and socialization, demonstrating that sleep phenotypes are associated with symptom severity in individuals with autism. This study provides foundational evidence for profiling and targeting sleep as a standard part of therapeutic intervention in individuals with autism.
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